Combinatorial processing enables rapid evaluation of, for example, semiconductor and solar processing operations. The systems supporting the combinatorial processing are flexible to accommodate the demands for running the different processes either in parallel, serial or some combination of the two.
Some exemplary processing operations include operations for adding (depositions) and removing layers (etch), defining features, preparing layers (e.g., cleans), conversion of layers or surfaces, doping, etc. Similar processing techniques apply to the manufacture of integrated circuit (IC) semiconductor devices, flat panel displays, switching devices like transistors or amorphous metal nonlinear resistor devices, optoelectronics devices, light-emitting devices, photovoltaic devices, thermoelectric devices, electrochromic devices, energy storage devices, energy efficiency coatings, haptic devices like touch screen devices, communication devices, wearable electronic devices, data storage devices, magneto electronic devices, magneto optic devices, packaged devices, and the like. As manufacturing processes continue to increase in complexity, improvements, whether in materials, unit processes, or process sequences, are continually being sought for the multi-step processing sequence.
However, semiconductor, thin-film-coating, architectural glass coating, and solar companies conduct research and development (R&D) on full wafer and (glass) substrate processing through the use of split lots, as the conventional deposition, etch, pattern, and conversion systems are designed to support this processing scheme. This approach has resulted in ever escalating R&D costs and the inability to conduct extensive experimentation in a timely and cost effective manner. Combinatorial processing as applied to semiconductor, solar, energy storage, lighting, display, haptics, or energy-efficiency manufacturing operations enables multiple experiments to be performed at one time in a high throughput manner. Equipment for performing the combinatorial processing and characterization must support the efficiency offered through the combinatorial processing operations. The debottlenecking of the R&D efforts involves the above fast processing platforms in combination with throughput-matched characterization and fast automated data capture and analysis, in addition to accelerated lifetime testing and product simulations to allow a fast guidance for subsequent design of experiments to unravel the correlations between materials, processing, equipment, and product performance and durability.